What is Data Management and Analysis?

Ivy May 15, 2014 No Comments

Data is everywhere whether in unstructured or structured form.  Yet stand alone data makes no sense unless measured, managed or optimised. To gain valuable insights into a given set of data, the data has to lend itself to analysis using a clearly defined methodology, strategy and business goals.

What this means.

Data is to be questioned, transformed into information and shaped to desired perspective.

Data cannot be ignored in any environment, be it a large enterprise, a local pizza delivery outlet, a municipality department, or in social science research.

Although how data is managed depends on the types of data involved, method of data collection, storage and usage; the entire process of data management and analysis uses various tools and software. These maybe query tools or automated and parameter-driven reporting tools integrated within a single common interface. Such tools help to slice and dice the data and analyse in unlimited number of ways – to identify patterns and establish relationships.

Why Data Management?

• Right tools and efficient use, help in time and cost efficiency.
• Facilitates handling of increased size of databases.
• Database from different data streams can be matched and integrated into a single database for analysis.
• Data also can be transformed into preferred electronic format for application ofvarious statistical packages.
• Field data can be cleaned and debugged for input and measurement errors, and reformatted.

To make sense of the data, and bring value to the organisation, data handling and management is critical.

Take for the instance the huge amount of unstructured as well as structured data being amassed by the TV Channels during the ongoing 2014 elections. Social media, sampling and historical data are integrated in a seamless platform to analyse trends and outcomes, for predictions. The entire process of elections analytics is possible because of efficient data management of the diverse raw data using an online analytical processing (OLAP) platform.

So, “a roadmap documenting the flow of data through the sequential phases of collection, storage, cleaning, reduction, analysis, and finally to archiving”, becomes part of data management and analysis.

Questions addressed:

Data Managament

How clean is the data? Does it need to be edited or re-formatted? Are techniques to be applied for reduction of duplication in the database records?

Is the data static? Will updates be available during the lifetime of data analysis?

How much data is to be managed and stored? Will all data be used for analysis, or only sub-sets of data used?

Data Analysis

Is the analysis well defined or exploratory? Are graphical capabilities needed?

Is the technique applied well-defined? Does the software compute necessary statistics or analysis or need to be developed?

Popular tools / softwares for data management and analysis:

While these are some popular “free” data analysis softwares used for a streamlined data management and analysis, others like the SPSS and SAS are also in demand.

Undoubtedly, each of these has its own capabilities, and can be leveraged for different data analysis goals.  While SPSS for data management and analysis  is used conventionally,  organsiations and social scientists are increasingly turning to the free statistical software, ‘R’ for the same.  ‘R’ wins hands down in preference, being free, and for its diverse packages that lend themselves to easy data input, management and analysis. R is easy to learn, use and implement. So go ahead and learn R for your data management and analysis needs.

 

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Why learning ‘R’ is important in the present day context?